Papers by Julia Romberg
Towards a Perspectivist Turn in Argument Quality Assessment (2025.naacl-long)
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| Challenge: | Argument quality is a key aspect of computational argumentation (CA), but it still exhibits a high degree of subjectivity in perception. |
| Approach: | They propose to use a multi-layered classification to target two aspects of argument quality in a systematic review of NLP datasets. |
| Outcome: | The proposed model improves the quality of annotators and their ability to be used in perspectivist research. |
A Corpus of German Citizen Contributions in Mobility Planning: Supporting Evaluation Through Multidimensional Classification (2022.lrec-1)
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| Challenge: | Political authorities in democratic countries consult the public in order to allow citizens to voice their ideas and concerns on specific issues. |
| Approach: | They propose a publicly-available corpus that includes citizen contributions from six mobility-related planning processes in five german municipalities. |
| Outcome: | The proposed corpus includes several thousand citizen contributions from six mobility-related planning processes in five German municipalities. |
Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It’s Best to Relate Perspectives! (2023.emnlp-main)
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| Challenge: | Existing approaches to subjectivity in natural language processing are subjective . authors argue that disagreement should not be regarded as a problem . |
| Approach: | They propose to account for subjective perspectives of individuals and objective concepts that build a common ground between annotators. |
| Outcome: | The proposed architectures increase the averaged annotator-individual F1-scores up to 43% over a majority-label model. |
Reassessing Active Learning Adoption in Contemporary NLP: A Community Survey (2026.eacl-long)
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| Challenge: | a longstanding strategy to reduce annotation costs is active learning . data annotation is expected to remain important and active learning to stay relevant . |
| Approach: | They conduct an online survey to assess the perceived relevance of data annotation and active learning . they propose a strategy to reduce annotation costs using active learning, an iterative process . |
| Outcome: | The proposed strategies reduce setup complexity and uncertainty cost while maintaining model performance. |